/pdf/design-of-distribution-transformer-health-management-system-3x070vp8hh.pdf

Design of Distribution Transformer Health Management System using IoT Sensors

The monitoring of Maximum Power Point (MPP) is a successful method for improving Photo Voltaic (PV) power extraction under different types of weather conditions. The power versus voltage curve shows multiple peaks as the PV module receives the different irradiances during the partial shading condition. In these situations, the Maximum Power Point Tracking (MPPT) capability to monitor the PV array's global MPP directly impacts system performance. Different approaches to MPPT were proposed in the literature. Among all, MPPT techniques based on Artificial Intelligence (AI) algorithms have established the potential to locate the MPP on a large scale. This work contributes a thorough and in-depth review of MPPT strategies based on AI. According to its application strategy, each method is categorized into one of several subcategories. The different techniques for incorporating AI into MPPTs are thoroughly examined with the thorough analysis of their merits and demerits. This study creates a set of MPPT techniques based on AI so that users can realize and choose the best approach for their needs and system constraints. 

Survey of AI based MPPT algorithms in PV systems

The monitoring of Maximum Power Point (MPP) is a successful method for improving Photo Voltaic (PV) power extraction under different types of weather conditions. The power versus voltage curve shows multiple peaks as the PV module receives the different irradiances during the partial shading condition. In these situations, the Maximum Power Point Tracking (MPPT) capability to monitor the PV array's global MPP directly impacts system performance. Different approaches to MPPT were proposed in the literature. Among all, MPPT techniques based on Artificial Intelligence (AI) algorithms have established the potential to locate the MPP on a large scale. This work contributes a thorough and in-depth review of MPPT strategies based on AI. According to its application strategy, each method is categorized into one of several subcategories. The different techniques for incorporating AI into MPPTs are thoroughly examined with the thorough analysis of their merits and demerits. This study creates a set of MPPT techniques based on AI so that users can realize and choose the best approach for their needs and system constraints.

This article introduces hybrid islanding technology for distributed generation (DG) based on inverters. This system depends on passive and active identification methods. The active island method produces interference at the DG output by continuously regenerating and injecting a feedback signal that depends on the implementation of the dq. On the other hand, the passive island method detects the island by controlling the frequency and voltage. This system uses a parallel connected RLC load. It has been shown that this control system is reliable, able to detect islands with a linear load and react quickly. Possible island conditions are simulated and checked 

Island Detection In Inverter Based Distributed Generation Using A Hybrid Method

This paper focuses on the design of a charging unit for an electric vehicle fast-charging station. Electric Vehicle is turning into a real alternative to conventional combustion-based vehicles due to their reduced greenhouse emissions. The conventional system experiences harmonic distortions, losses and takes more time to charge. To overcome these problems, new methods and techniques are established here. With the help of a bidirectional-based converter, electric vehicle charging stations offer quick charging. When using a three-phase supply, phase voltage is given to the suggested converter. In conventional type converters, harmonic distortions are inherent; however, we can lessen voltage distortions by employing bidirectional converters. When tested with a prototype model featuring the suggested converter, the voltage ripple factor is quite low. Phase-shifting pulse width modulation is the topology employed in this procedure. The output voltages are controlled by a precise and simple algorithm. We can also use artificial intelligence gadgets to improve the circuit in the future. By comparing the input and output voltages in the feedback system, we can eliminate both steady-state and transient errors. The charging stations implemented in various areas are used effectively for efficiently charging Electric vehicles. The number of components is reduced compared to traditional converters and thus increasing the efficiency of bi-directional converters with less cost. This charger is also verified for fluctuations in power supply and supply voltages with higher magnitudes. The proposed charger gives us improved power factor and efficiency.

Partial Power Processing Based Bidirectional Converter for Electric Vehicle Fast Charging Stations

In this paper, we examine the microgrids and the long-term dynamic capacity expansion planning in their architecture. Many resources contribute towards the supply to microgrid such as energy, micro gas turbine, solar and wind storage system. Moreover the electric vehicle charging stations use these microgrids as a source of electricity. The electric vehicles that are used in charging stations are based on vehicle-to-grid wherein it is possible to regulate the charging rate and time and to transmit energy to the microgrid. Hence, these charging stations are found to be present in generating unit or flexible load. In the microgrid, the capacity expansion planning is initiated to expand the capacity of battery, wind turbine, solar and micro turbine energy storage system. We have elaborated a 6–year planning horizon, targeting a long term plan through capacity expansion. On the other hand, we have also conducted a short term plan simultaneously to improve the hourly operation of electric vehicle charging station, energy and micro turbine storage system. An expansion of about 200% on wind system is used such that expansion cost is about 53% and incorporation of further resources will increase it by 58% in terms of cost.

https://irojournals.com/iroeea/V3/I1/06.pdf

Energy Storage Capacity Expansion of Microgrids for a Long-Term

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Energy Storage Capacity Expansion of Microgrids for a Long-Term